B. Rosner et Rj. Glynn, MULTIVARIATE METHODS FOR CLUSTERED ORDINAL DATA WITH APPLICATIONS TO SURVIVAL ANALYSIS, Statistics in medicine, 16(4), 1997, pp. 357-372
Clustered data are the rule in many clinical specialties such as ophth
almology. Methods have been developed for the treatment of clustered c
ontinuous or binary outcome data. Less attention has been given to ord
inal outcomes which occur frequently in ophthalmology. For example, gr
ading systems of cataract and diabetic retinopathy are commonly used w
here a photograph is graded by comparison with a series of reference p
hotographs of increasing severity. Some commonly used methods for the
analysis of ordered categorical data include the proportional odds and
continuation ratio models. It is difficult, however, to incorporate c
lustering effects into these models. Instead, for clusters of size two
, we propose a generalization of the adjacent category model given by
log [Pr(i + 1,j)/Pr(i,j)] = u(i) + (j - 1)lambda + beta'x, where Pr(i,
j) denotes the probability that the right (left) eye has grade i(j), x
is a vector of(person or eye-specific) covariates for the right eye,
u and beta are vectors of location and covariate parameters and lambda
is a clustering parameter. Based on this model, and a similar model i
nterchanging the role of i and j, we derive a closed-form expression f
or Pr(i,j) as a function of u, lambda, and beta and use Newton-Raphson
methods to maximize the likelihood. An extension of the method allows
for extra agreement along the diagonal and is then a generalization o
f the agreement plus linear-by-linear association model proposed by Ag
resti in the setting of no covariates. We apply these methods to a dat
a set of 43 diabetic subjects from the Harvard Clinical Cataract Resea
rch Center, where cortical cataract grade was the outcome. We also ext
end this methodology to a survival setting, where both censored and un
censored outcomes are available for individual cluster members, and on
e wishes to take clustering into account. We apply the survival analys
is model to a data set of 1807 children (two ears per child) in the gr
eater Boston area, who were followed for the development of otitis med
ia over the first year of life.